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Python Deep Learning

You're reading from   Python Deep Learning Understand how deep neural networks work and apply them to real-world tasks

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Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781837638505
Length 362 pages
Edition 3rd Edition
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Author (1):
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Ivan Vasilev Ivan Vasilev
Author Profile Icon Ivan Vasilev
Ivan Vasilev
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Table of Contents (17) Chapters Close

Preface 1. Part 1:Introduction to Neural Networks
2. Chapter 1: Machine Learning – an Introduction FREE CHAPTER 3. Chapter 2: Neural Networks 4. Chapter 3: Deep Learning Fundamentals 5. Part 2: Deep Neural Networks for Computer Vision
6. Chapter 4: Computer Vision with Convolutional Networks 7. Chapter 5: Advanced Computer Vision Applications 8. Part 3: Natural Language Processing and Transformers
9. Chapter 6: Natural Language Processing and Recurrent Neural Networks 10. Chapter 7: The Attention Mechanism and Transformers 11. Chapter 8: Exploring Large Language Models in Depth 12. Chapter 9: Advanced Applications of Large Language Models 13. Part 4: Developing and Deploying Deep Neural Networks
14. Chapter 10: Machine Learning Operations (MLOps) 15. Index 16. Other Books You May Enjoy

Exploring model deployment

In this section, we’ll discuss two basic model deployment examples. They’ll help you create simple, yet functional, proof-of-concept apps for your experiments. Let’s start.

Deploying NN models with Flask

In our first example, we’ll use Google Colab in combination with Flask (https://github.com/pallets/flask) to create a simple hosted REST API service, which will expose our model to the outside world. For the sake of simplicity, we’ll use a stable diffusion (SD) model: it will accept a textual prompt parameter, generate an image with it, and return the image as a result.

According to its home page, Flask is a lightweight WSGI (https://wsgi.readthedocs.io/) web application framework. It is designed to make getting started quick and easy, with the ability to scale up to complex applications. In our case, it will start a development web server, which will process the requests for the SD model. Although this server will...

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